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Record W2762143131 · doi:10.1093/pch/19.6.e35-8

8: Early Oral Feeding for Very Low Birthweight Neonates Maintained on Continuous Positive Airway Pressure for Lung Optimization is Feasible

2014· article· en· W2762143131 on OpenAlexaff
SR Dalgleish, Linda Kostecky

Bibliographic record

VenuePaediatrics & Child Health · 2014
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsMedicineContinuous positive airway pressureBreastfeedingBronchopulmonary dysplasiaPediatricsNeonatal intensive care unitContraindicationFunctional residual capacityGestational ageIntensive care medicineLung volumesAnesthesiaLungPregnancyInternal medicineObstructive sleep apnea

Abstract

fetched live from OpenAlex

Low birth weight neonates in the neonatal intensive care unit (NICU) are commonly managed with early and prolonged continuous positive airway pressure (CPAP). CPAP therapy is used to maintain functional residual capacity and allow the lungs to grow at optimized inflation. Historically, CPAP has been considered a contraindication for initiation of oral feeding. Delayed introduction of oral feeding is associated with delayed progression of oral feeding skills. Although prolonged CPAP has lessened the burden of bronchopulmonary dysplasia (BPD), oral feeding delay has resulted in longer NICU stays and increased the potential for long term feeding problems. To study the clinical feasibility of initiating early oral feeding for neonates who are CPAP dependent. Physiological stability and infant cues guide the nursing assessment for oral readiness. Breastfeeding is encouraged and preferred method of feeding. Emerging evidence suggests such a technique encourages the neonate to associate food and eating with safety and pleasure. We report a quality improvement project designed as an observational study. An original algorithm called “Eating “in SINC” (Safe Individualized Nipple-feeding Competence) was introduced for all neonates <32 weeks' corrected gestational age who have been on CPAP. The SINC algorithm encourages frequent oral feeding practice opportunities, specifies maximum oral feeding volumes and limits oral feeding times with a goal of building skill and stamina in fragile feeders. Breastfeeding is encouraged at every stage of the algorithm. Progression in the SINC algorithm is allowed only if the neonate displays competency over a number of days. The intervention group eating with the SINC algorithm (collected over a six month period) is compared to a historical cohort of neonates from a similar time period during which time the neonates were maintained on prolonged CPAP for lung optimization but did not receive any oral feeding while on CPAP therapy. Early project results support our SINC algorithm. Neonates can be maintained on CPAP to prevent BPD and oral feeding can be safely initiated at the same time. Overall length of stay has been reduced between the two comparative groups. Breast feeding rates and oral feeding difficulties following discharge from the NICU are being tracked. It is possible to maintain prolonged CPAP for lung optimization in very low birth weight neonates and initiate safe early oral feeding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.318
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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